.gitignore

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-output/
-env/
-tools/__pycache__/
-tools/config.json

README.md

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 # memegraph
 I previously did meme generation via Langchain in https://github.com/runyanjake/memechain. Here is the same project but written using Langgraph instead, since that seems to have superseded Langchain in recent time.
-
-The main reason to make the switch is to explore [multi-agent](https://github.com/langchain-ai/langgraph/blob/main/docs/docs/tutorials/multi_agent/multi-agent-collaboration.ipynb) workflows, which hopefully we can apply to this project at some point.
-
-## Setup 
-
-### Python 
-```
-python3 -m venv env
-source env/bin/activate
-pip install -r requirements.txt
-python main.py
-...
-deactivate
-```
-
-## Usage 
-Can specify prompt when calling script or will use default prompt.
-```
-python main.py 
-python main.py --prompt "Generate an image for the 'Leonardo dicaprio cheers' meme with the text 'LANGGRAPH MEMES'."
-```

main.py

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-from langchain_ollama.llms import OllamaLLM
-from langchain_core.output_parsers import PydanticOutputParser
-from langgraph.graph import StateGraph, END
-
-from pydantic import BaseModel, Field
-
-from tools.get_memes import get_memes
-from tools.caption_image import caption_image
-from tools.download_image import download_image
-
-from typing import TypedDict, Optional
-
-import argparse
-import json
-import re 
-
-############################# State Definition ################################
-class State(TypedDict):
-    question: str
-    template_name: Optional[str]
-    text: Optional[list[str]]
-    template_id: Optional[int]
-    caption_result: Optional[dict]
-    image_path: Optional[str]
-
-############################# LLM Definition ##################################
-llm = OllamaLLM(model="llama3")
-
-class MemeInfo(BaseModel):
-    template_name: str = Field(..., description="The meme template name")
-    text: list[str] = Field(..., description="List of captions/texts for the meme")
-
-parser = PydanticOutputParser(pydantic_object=MemeInfo)
-
-def parse_input(state: State) -> State:
-    prompt = f"""
-    Extract the meme name and list of texts from the user's request. 
-    Return the output in this JSON format:
-
-    {parser.get_format_instructions()}
-
-    User input: {state["question"]}
-    """
-
-    response = llm.invoke(prompt)
-    parsed = parser.invoke(response)
-    print(parsed)
-    return {**state, **parsed.model_dump()}
-
-######################## Graph Components Definition ##########################
-def node_get_memes(state: State) -> State:
-    memes_str = get_memes()
-    memes = memes_str.strip().splitlines()
-
-    for meme in memes:
-        match = re.match(r"ID: (\d+), Name: (.+)", meme)
-        if match:
-            meme_id = int(match.group(1))
-            meme_name = match.group(2).strip()
-
-            if meme_name.lower() == state["template_name"].lower():
-                print("Found Meme: " + meme)
-                return {**state, "template_id": meme_id}
-
-    raise ValueError(f"No matching meme found for template_name: {state['template_name']}\nAvailable Memes:\n{memes}")
-
-def node_caption_image(state: State) -> State:
-    input_data = {
-        "template_id": int(state["template_id"]),
-        "text": state["text"]
-    }
-    json_input = json.dumps(input_data)
-    result = caption_image(json_input)
-    print(result)
-    return {**state, "caption_result": result}
-
-def node_download_image(state: State) -> State:
-    image_url = state["caption_result"]
-    if isinstance(image_url, str) and image_url.startswith("http"):
-        download_payload = json.dumps({"url": image_url})
-        result = download_image(download_payload)
-        return {**state, "image_path": result}
-    else:
-        print("Failed to download image. " + image_url)
-
-############################## Graph Definition ###############################
-graph = StateGraph(State)
-
-graph.add_node("parse_input", parse_input)
-graph.add_node("get_memes", node_get_memes)
-graph.add_node("caption_image", node_caption_image)
-graph.add_node("download_image", node_download_image)
-
-graph.set_entry_point("parse_input")
-graph.add_edge("parse_input", "get_memes")
-graph.add_edge("get_memes", "caption_image")
-graph.add_edge("caption_image", "download_image")
-graph.add_edge("download_image", END)
-
-app = graph.compile()
-
-#################################### Run ######################################
-def main():
-    parser = argparse.ArgumentParser(description="Meme Generation Script")
-    parser.add_argument(
-        "--prompt", 
-        type=str, 
-        help="Optional prompt for the meme generation", 
-        default="Generate an image for the 'two buttons' meme with first text 'generated meme' and second text 'langgraph error'."
-    )
-    args = parser.parse_args()
-    
-    question = args.prompt
-    final_state = app.invoke({"question": question})
-    print(final_state["image_path"])
-
-if __name__ == "__main__":
-    main()
-

requirements.txt

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-langchain_community
-langchain_core>=0.1.35
-langchain_experimental
-langchain_ollama
-langgraph
-pillow
-pydantic

tools/caption_image.py

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-import json
-import requests
-
-CAPTION_IMAGE_URL = "https://api.imgflip.com/caption_image"
-
-def load_config():
-    with open('tools/config.json') as config_file:
-        return json.load(config_file)   
-
-def caption_image(input_data):
-    # Replace single quotes with double quotes because langchain likes to use single quotes
-    input_data = input_data.replace("'", '"')
-    
-    data = json.loads(input_data)
-    template_id = data['template_id']
-    text = data['text']
-
-    config = load_config()
-    username = config['username']
-    password = config['password']
-
-    url = CAPTION_IMAGE_URL
-    payload = {
-        "template_id": template_id,
-        "username": username,
-        "password": password,
-    }
-    
-    for i in range(len(text)):
-        payload[f'text{i}'] = text[i]
-
-    response = requests.post(url, data=payload)
-    result = response.json()
-
-    if result['success']:
-        meme_url = result['data']['url']
-        print(f"Meme created! URL: {meme_url}")
-        return meme_url
-    else:
-        return None

tools/config.json.blanked

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-{
-  "username":"xxxx",
-  "password":"yyyy"
-}

tools/download_image.py

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-import os
-import requests
-import json
-
-def download_image(input_data):
-    input_data = input_data.replace("'", '"')
-    
-    data = json.loads(input_data)
-    url = data['url']
-
-    response = requests.get(url)
-    if response.status_code == 200:
-        output_dir = 'output'
-        os.makedirs(output_dir, exist_ok=True)
-        image_path = os.path.join(output_dir, url.split("/")[-1])
-        with open(image_path, 'wb') as f:
-            f.write(response.content)
-        print(f"Image saved to {image_path}")
-        return image_path
-    else:
-        print("Failed to download image.")
-        return None

tools/get_memes.py

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-import requests
-
-GET_MEMES_URL = "https://api.imgflip.com/get_memes"
-
-def get_memes():
-    return get_memes_helper()
-
-def get_memes_helper():
-    response = requests.get(GET_MEMES_URL)
-    result = response.json()
-
-    if result['success']:
-        memes = result['data']['memes']
-        memes_str = "\n".join([f"ID: {meme['id']}, Name: {meme['name']}" for meme in memes])
-        return memes_str
-    else:
-        return "No template_ids found."
-